CA3045324A1 - Systeme et procede de commande de systeme de stockage d'energie dynamique - Google Patents

Systeme et procede de commande de systeme de stockage d'energie dynamique Download PDF

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Publication number
CA3045324A1
CA3045324A1 CA3045324A CA3045324A CA3045324A1 CA 3045324 A1 CA3045324 A1 CA 3045324A1 CA 3045324 A CA3045324 A CA 3045324A CA 3045324 A CA3045324 A CA 3045324A CA 3045324 A1 CA3045324 A1 CA 3045324A1
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CA
Canada
Prior art keywords
neural network
energy
energy storage
artificial neural
storage system
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CA3045324A
Other languages
English (en)
Inventor
Yiran Li
Peisen HU
Derek Lim SOO
Matthew SACHS
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Peak Power Inc
Original Assignee
Peak Power Inc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Peak Power Inc filed Critical Peak Power Inc
Publication of CA3045324A1 publication Critical patent/CA3045324A1/fr
Pending legal-status Critical Current

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Classifications

    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • G—PHYSICS
    • G05—CONTROLLING; REGULATING
    • G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B13/00—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion
    • G05B13/02—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric
    • G05B13/0265—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion
    • G05B13/029—Adaptive control systems, i.e. systems automatically adjusting themselves to have a performance which is optimum according to some preassigned criterion electric the criterion being a learning criterion using neural networks and expert systems
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/004—Artificial life, i.e. computing arrangements simulating life
    • G06N3/006—Artificial life, i.e. computing arrangements simulating life based on simulated virtual individual or collective life forms, e.g. social simulations or particle swarm optimisation [PSO]
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
    • G06Q50/06—Electricity, gas or water supply
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00—Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/00032—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for
    • H02J13/00034—Systems characterised by the controlled or operated power network elements or equipment, the power network elements or equipment not otherwise provided for the elements or equipment being or involving an electric power substation
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/003—Load forecast, e.g. methods or systems for forecasting future load demand
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00—Circuit arrangements for ac mains or ac distribution networks
    • H02J3/28—Arrangements for balancing of the load in a network by storage of energy
    • H02J3/32—Arrangements for balancing of the load in a network by storage of energy using batteries with converting means
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • G06N20/10—Machine learning using kernel methods, e.g. support vector machines [SVM]
    • H—ELECTRICITY
    • H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
    • H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02B—CLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO BUILDINGS, e.g. HOUSING, HOUSE APPLIANCES OR RELATED END-USER APPLICATIONS
    • Y02B90/00—Enabling technologies or technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02B90/20—Smart grids as enabling technology in buildings sector
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/50—Energy storage in industry with an added climate change mitigation effect
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00—Systems supporting electrical power generation, transmission or distribution
    • Y04S10/14—Energy storage units
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S20/00—Management or operation of end-user stationary applications or the last stages of power distribution; Controlling, monitoring or operating thereof

Abstract

Un système de commande permettant de commander un système de stockage d'énergie comprend un dispositif de commande comprenant une pluralité de nuds en couches configurés pour former un réseau de neurones artificiels entraîné pour générer une charge de niveau de transmission prévue et une valeur de confiance pour une juridiction entière d'un système de distribution de services publics. Le dispositif de commande comprend au moins une mémoire et au moins un processeur configuré pour : identifier un pic coïncidant potentiel pour le système de distribution de services publics sur la base de la charge de niveau de transmission prévue et de la valeur de confiance générées par le réseau de neurones artificiels ; et lors de l'identification d'un pic coïncidant potentiel, transmettre des signaux pour amener l'infrastructure électrique à consommer l'énergie stockée au niveau du système de stockage d'énergie, ce qui permet de réduire l'énergie tirée à partir du système de distribution de services publics pendant le pic coïncidant potentiel identifié.
CA3045324A 2016-11-29 2017-11-29 Systeme et procede de commande de systeme de stockage d'energie dynamique Pending CA3045324A1 (fr)

Applications Claiming Priority (3)

Application Number Priority Date Filing Date Title
US201662427199P 2016-11-29 2016-11-29
US62/427,199 2016-11-29
PCT/CA2017/051435 WO2018098575A1 (fr) 2016-11-29 2017-11-29 Système et procédé de commande de système de stockage d'énergie dynamique

Publications (1)

Publication Number Publication Date
CA3045324A1 true CA3045324A1 (fr) 2018-06-07

Family

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Family Applications (1)

Application Number Title Priority Date Filing Date
CA3045324A Pending CA3045324A1 (fr) 2016-11-29 2017-11-29 Systeme et procede de commande de systeme de stockage d'energie dynamique

Country Status (6)

Country Link
US (1) US10873209B2 (fr)
EP (1) EP3549234A4 (fr)
JP (2) JP7051856B2 (fr)
AU (1) AU2017368470B2 (fr)
CA (1) CA3045324A1 (fr)
WO (1) WO2018098575A1 (fr)

Families Citing this family (18)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
KR102089772B1 (ko) * 2017-12-18 2020-03-17 두산중공업 주식회사 전력 사용량 예측 시스템 및 방법
EP3824677A1 (fr) * 2018-07-19 2021-05-26 Telefonaktiebolaget Lm Ericsson (Publ) Procédé et dispositifs pour optimiser une commande d'alimentation de secours à l'aide d'un apprentissage automatique
US11461112B2 (en) 2019-02-07 2022-10-04 International Business Machines Corporation Determining feature settings for code to deploy to a system by training a machine learning module
US10862302B1 (en) * 2019-07-01 2020-12-08 Oracle International Corporation Intelligent data preprocessing technique to facilitate loadshape forecasting for a utility system
CN110535146B (zh) * 2019-08-27 2022-09-23 哈尔滨工业大学 基于深度确定策略梯度强化学习的电力系统无功优化方法
US11444473B2 (en) 2019-10-15 2022-09-13 Inventus Holdings, Llc Dynamic battery charging for maximum wind/solar peak clipping recapture
KR102253736B1 (ko) * 2019-11-26 2021-05-20 주식회사 비엠티 인공신경망을 이용한 재귀적 전력 수요 예측 방법
KR102253741B1 (ko) * 2019-11-26 2021-05-20 주식회사 비엠티 인공신경망을 이용한 다중적 전력 수요 예측 방법
CN111443615A (zh) * 2020-04-09 2020-07-24 南方电网科学研究院有限责任公司 一种用电设备控制系统、方法以及设备
CN113872180A (zh) * 2020-06-30 2021-12-31 华为技术有限公司 设备供电的方法、系统及相关设备
EP4213089A1 (fr) * 2020-09-07 2023-07-19 Daikin Industries, Ltd. Dispositif d'apprentissage de charge de climatisation et dispositif de prédiction de charge de climatisation
JP7125644B2 (ja) * 2020-09-07 2022-08-25 ダイキン工業株式会社 空調負荷学習装置、空調負荷予測装置
CN112564186B (zh) * 2020-12-11 2022-06-14 中国电力科学研究院有限公司 一种辅助火电机组深度调峰的储能功率及容量规划方法及系统
CN113078648B (zh) * 2021-03-31 2024-02-09 安徽尚特杰电力技术有限公司 一种基于微网控制器的系统能量调度优化方法及系统
CN113219871B (zh) * 2021-05-07 2022-04-01 淮阴工学院 一种养护室环境参数检测系统
US20230275455A1 (en) * 2022-02-25 2023-08-31 Peak Power, Inc. Systems and Methods of Energy Storage System Operation
CN116632841A (zh) * 2023-07-26 2023-08-22 国网山东省电力公司信息通信公司 融合多时序特征的配电台区短期用电负荷预测方法及系统
CN117254586A (zh) * 2023-09-14 2023-12-19 山东华科信息技术有限公司 一种分布式能源并网监测调控系统

Family Cites Families (17)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4914603A (en) * 1988-12-14 1990-04-03 Gte Laboratories Incorporated Training neural networks
JP3599387B2 (ja) * 1994-11-07 2004-12-08 東京電力株式会社 電力貯蔵システム
JP4864839B2 (ja) 2007-08-27 2012-02-01 株式会社東芝 電力変動予測システム
WO2009029777A1 (fr) * 2007-08-31 2009-03-05 Powerit Solutions, Llc Contrôleur de demande de pointe automatisé
US8548638B2 (en) * 2008-09-15 2013-10-01 General Electric Company Energy management system and method
US9134353B2 (en) * 2009-02-26 2015-09-15 Distributed Energy Management Inc. Comfort-driven optimization of electric grid utilization
JP5659486B2 (ja) 2009-12-17 2015-01-28 富士電機株式会社 発電計画作成方法および発電計画作成システム
JP2012249458A (ja) * 2011-05-30 2012-12-13 Sony Corp 電力供給装置および電力供給制御方法
US20130030590A1 (en) * 2011-07-29 2013-01-31 Green Charge Networks Llc Peak Mitigation Extension Using Energy Storage and Load Shedding
US20120150679A1 (en) * 2012-02-16 2012-06-14 Lazaris Spyros J Energy management system for power transmission to an intelligent electricity grid from a multi-resource renewable energy installation
US9438041B2 (en) * 2012-12-19 2016-09-06 Bosch Energy Storage Solutions Llc System and method for energy distribution
US9852481B1 (en) * 2013-03-13 2017-12-26 Johnson Controls Technology Company Systems and methods for cascaded model predictive control
WO2014197931A1 (fr) * 2013-06-12 2014-12-18 Applied Hybrid Energy Pty Ltd Procédé et système de régulation d'énergie électrique
CN103545843B (zh) 2013-11-06 2014-11-19 国家电网公司 微电网离网协调控制方法
JP2015192586A (ja) 2014-03-31 2015-11-02 株式会社明電舎 マイクログリッドの需給制御システムおよび需給制御方法
US20170373500A1 (en) * 2014-12-22 2017-12-28 Robert Bosch Gmbh Method for Adaptive Demand Charge Reduction
JP6079803B2 (ja) * 2015-03-20 2017-02-15 ダイキン工業株式会社 デマンドレスポンス制御結果提示装置

Also Published As

Publication number Publication date
AU2017368470A1 (en) 2019-07-11
AU2017368470B2 (en) 2022-09-15
JP2020501491A (ja) 2020-01-16
EP3549234A1 (fr) 2019-10-09
WO2018098575A1 (fr) 2018-06-07
EP3549234A4 (fr) 2020-04-22
US20190312457A1 (en) 2019-10-10
JP7051856B2 (ja) 2022-04-11
JP2022104955A (ja) 2022-07-12
US10873209B2 (en) 2020-12-22

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